{"id":"W3135131585","doi":"10.21700/ijcis.2016.110","title":"Automatic Fall Detection System using Sensing Floors","year":2016,"lang":"en","type":"article","venue":"International Journal of Computing and Information Sciences","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Feature selection; Computer science; Autonomy; Accelerometer; Feature (linguistics); Feature extraction; Independence (probability theory); Computer security; Real-time computing; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002328821,0.0007591788,0.0009519265,0.001267174,0.0003588514,0.0005232051,0.0006809423,0.0004945492,0.003107674],"category_scores_gemma":[0.0006350874,0.0003416172,0.0003705952,0.0006568087,0.0001638173,0.0004849108,0.0007266194,0.0002452928,0.001441586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001601979,"about_ca_system_score_gemma":0.0003257546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001334536,"about_ca_topic_score_gemma":0.001728168,"domain_scores_codex":[0.999617,0.00004244451,0.00002996752,0.0001067186,0.0001495399,0.00005438659],"domain_scores_gemma":[0.9996829,0.00003825188,0.00003902007,0.00004070463,0.0001602851,0.00003895782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001284811,0.0004296656,0.01941468,0.0004264488,0.0001148608,0.0006435713,0.0002667709,0.01080646,0.2385439,0.0007857392,0.009447957,0.7178352],"study_design_scores_gemma":[0.0002800349,0.001557603,0.08895113,0.0001394716,0.0002564725,0.001646181,0.0003930137,0.7533063,0.1340233,0.002383694,0.01685908,0.0002037734],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3982168,0.001397153,0.571779,0.0002885112,0.0005202019,0.0003956065,0.00148337,0.01794142,0.007977864],"genre_scores_gemma":[0.8796411,0.0003730025,0.114519,0.0001315098,0.00008723063,0.0002217838,0.0009523167,0.00008933603,0.003984752],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003107674,"threshold_uncertainty_score":0.01039618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02442447684499856,"score_gpt":0.2827711461143648,"score_spread":0.2583466692693662,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}